1514.8.2 Arctic
This section is concerned with temperature and precipitation dimensions of Arctic climate change, and their links to climate phenomena. The reader is referred elsewhere for information on sea ice loss (Sections 4.2.2, 5.5.2 and Chapter 10), and projections of sea ice change (Sections 9.4.3, 9.8.3 and Chapters 11 and 12). Arctic climate is affected by three modes of variability: NAO (Section 14.5.1), PDO (Section 14.7.3) and AMO (Section 14.7.6). The NAO index correlates positively with temperatures in the northeastern Eurasian sector, and correlates negatively with temperatures in the Baffin Bay and Canadian Archipelago, but exhibits little relationship with central Arctic temperatures (Polyakov et al., 2003). The PDO plays a role in temperature variability of Alaska and the Yukon (Hartmann and Wendler, 2005). The AMO is positively associated with SST throughout the Arctic (Chylek et al., 2009; Levitus et al., 2009; Chylek et al., 2010) (Mahajan et al., 2011). ETCs are also mainly responsible for winter precipitation in the region (see Table 14.3). The surface and lower troposphere in the Arctic and surrounding land areas show regional warming over the past three decades of about 1°C per decade—significantly greater than the global mean trend (Figures 2.22 and 2.25). According to temperature reconstructions, this signal is highly unusual: Temperatures averaged over the Arctic over the past few decades are significantly higher than any seen over the past 2000 years (Kaufman et al., 2009). Temperatures 11 ka were greater than the 20th century mean, but this is probably a strongly forced signal, since summer solar radiation was 9% greater than present (Miller et al., 2010). Finally, warmer temperatures have been sustained in pan-Arctic land areas where a declining NAO over the past decade ought to have caused cooling (Semenov, 2007; Turner et al., 2007b). Since AR4, evidence has also emerged that precipitation has trended upward in most pan-Arctic land areas over the past few decades (e.g., Pavelsky and Smith, 2006; Rawlins et al., 2010), though the evidence remains mixed (e.g., Dai et al., 2009). Increasing ETC activity over the Canadian Arctic has also been observed (Section 2.6.4). Since AR4, there has been progress in adapting RCMs for polar applications (Wilson et al., 2012). These models have been evaluated with regard to their ability to simulate Arctic clouds, surface heat fluxes, and boundary layer processes (Tjernstrom et al., 2004; Inoue et al., 2006; Rinke et al., 2006). They have been used to improve simulations of Arctic-specific climate processes, such as glacial mass balance (Zhang et al., 2007). A few regional models have been used for Arctic climate change projections (e.g., Zahn and von Storch, 2010; Koenigk et al., 2011; Döscher and Koenigk, 2012). For information on GCM quality in the Arctic, see Chapter 9 and the brief summary of assessed confidence in the CMIP5 models in Table 14.2. The CMIP5 model simulations exhibit an ensemble-mean polar amplified warming, especially in winter, similar to CMIP3 model simulations (Bracegirdle and Stephenson, 2012; see also Box 5.1). For RCP4.5, ensemble-mean winter warming rises to 5.0°C over pan-Arctic land areas by the end of the 21st century (2081–2100), and about 7.0°C over the Arctic Sea (Table14.1). Throughout the century, the warming exceeds simulated estimates of internal variability (Figure AI.8). The RCP4.5 ensemble-mean warming is more modest in JJA (Table 14.1) reaching about 2.2°C by century’s end over pan-Arctic land areas, and 1.5°C over the Arctic Sea. The summer warming exceeds variability estimates by about mid-century (Figure AI.9). These simulated anthropogenic seasonal warming patterns match qualitatively the observed warming patterns over the past six decades (AMAP, 2011), and the observed warming patterns are likely to be at least partly anthropogenic in origin (Section 10.3.1.1.4). Given the magnitude of future projected changes relative to variability, and the presence of anthropogenic signals already, it is likely future Arctic surface temperature changes will continue to be strongly influenced by the anthropogenic forcing over the coming decades. The CMIP5 models robustly project precipitation increases in the pan-Arctic (both land and sea) region over the 21st century, as did their CMIP3 counterparts (Kattsov et al., 2007; Rawlins et al., 2010). Under the RCP4.5 scenario, the cold season, ensemble mean precipitation increases about 25% by the century’s end (Table 14.1), due to enhanced precipitation in ETCs (Table 14.3). However, this signal does not rise consistently above the noise of simulated variability until mid 21st century (Figure AI.10). During the warm season, precipitation increases are smaller, about 15% (Table 14.1), though these signals also rise above variability by mid 21st century (Figure AI.11). The inter-model spread in the precipitation increase is generally as large as the ensemble mean signal itself (similar to CMIP3 model behaviour, Holland and Webster, 2007), so the magnitude of the future increase is uncertain. However, since nearly all models project a large precipitation increase rising above the variability year-round, it is likely the pan-Arctic region will experience a statistically significant increase in precipitation by mid-century (see also Table 14.2). The small projected increase in the NAO is likely to affect Arctic precipitation (and temperature) patterns in the coming century (Section 14.5.1; Table 14.3), though the importance of these signals relative to anthropogenic signals described here is unclear. In summary: It is likely Arctic surface temperature changes will be strongly influenced by anthropogenic forcing over the coming decades dominating natural variability such as induced by NAO. It is likely the pan-Arctic region will experience a significant increase in precipitation by mid-century due mostly to enhanced precipitation in ETCs.